Senior Software Engineer working on large-scale backend and ML data infrastructure. Focused on system design, reliability, performance, and cloud cost optimization. Own critical components end-to-end and contribute to architectural decisions across teams.

Worked on machine learning data infrastructure, including data streaming systems and multi-petabyte data lake management and tooling.

• Led the data platform team responsible for building and operating an in-house event pipeline supporting product analytics and downstream consumers.

• Owned the technical direction and architecture for event ingestion, processing, and storage across Kafka-based systems.

• Partnered with product and engineering teams to define event contracts and ensure reliable, scalable data flows.

• Built and maintained data tooling and pipelines leveraging Kafka and Snowflake to support analytics and business reporting.

• Drove improvements in reliability, observability, and developer workflows across the data platform

• Designed and built core components of Cameo’s data platform, supporting real-time and batch data use cases.

• Implemented event-driven pipelines using Kafka to ingest and process high-volume application data.

• Deployed and operated services on Kubernetes, contributing to platform reliability and scalability.

• Improved CI/CD workflows using Jenkins to streamline deployments and reduce operational friction.

• Collaborated cross-functionally to evolve the data architecture as product requirements scaled.

• Built data-intensive applications and pipelines using Python, Scala, Spark, and Akka.

• Implemented streaming and batch data processing workflows using Kafka and Spark.

• Contributed to distributed systems handling large-scale data processing and analytics workloads.

• Worked closely with stakeholders to translate data requirements into scalable technical solutions.